{"categories":[{"label":"Utilities","url":"https://skillfed.io/packages/category/utilities/7"}],"enrichment":{"capability":"Adds technical analysis indicators and statistics to pandas DataFrames for stock market data, including moving averages, momentum, trend, volatility, and volume calculations.","skillfed_tags":["technical-analysis","financial-data","trading-indicators"],"use_cases":["Build trading signal detection systems by accessing RSI, MACD, or Bollinger Bands to identify overbought/oversold conditions and trend reversals.","Analyze historical stock data with cross-over detection (e.g., golden cross of 10-period and 50-period SMAs) to backtest trading strategies.","Generate multi-indicator dashboards by wrapping pandas data and accessing dozens of indicators with simple column access patterns.","Calculate momentum and volatility metrics (Stochastic RSI, ATR, CCI) for risk assessment and position sizing in algorithmic trading.","Detect trend changes using Supertrend, Aroon, Ichimoku, or DMI indicators to automate entry and exit signals."],"what_it_does":"stockstats wraps pandas DataFrames to add inline technical analysis indicators commonly used in stock trading and financial analysis. It provides a large library of pre-built indicators\u2014moving averages (SMA, EMA, SMMA, TEMA, LRMA, KAMA, VWMA, DMA), momentum oscillators (RSI, MACD, Stochastic, KDJ, ROC, CMO, KST, Coppock, AO, BOP, CTI, Inertia, PSL), trend indicators (Supertrend, Aroon, Ichimoku, DMI, TRIX, Wave Trend), volatility measures (Bollinger Bands, ATR, CCI, Williams %R, CHOP, KER, Z-Score, MAD, PGO), volume analysis (VR, MFI, PVO, VWMA), and oscillators (QQE, RVGI, ERI, FTR)\u2014plus utility functions for delta, shifts, log returns, and cross-over detection.\n\nYou initialize it by wrapping a pandas DataFrame containing standard OHLCV columns (close, high, low, volume, optionally date), then access indicators by column name patterns like `df['rsi']` or `df['close_20_sma']`. Indicators are calculated on first access and cached; you can delete a column to force re-evaluation. Multi-line indicators like MACD and Bollinger Bands generate multiple columns at once. The library supports Python 3.9+ and has no compiled dependencies.","worth_installing":"Yes. stockstats is actively maintained, has no security vulnerabilities, low install friction, and a permissive license. It provides a comprehensive, well-documented library of technical indicators for stock analysis. Install it if you need to add technical analysis to pandas-based financial workflows; skip it only if you require indicators not in its supported list or need real-time streaming optimizations."},"id":"stockstats","links":{"html":"https://skillfed.io/packages/stockstats","md":"https://skillfed.io/packages/stockstats.md","pypi":"https://pypi.org/project/stockstats/"},"maintenance":{"status":"active"},"meta":{"latest_release":"2026-02-16","license_spdx":"BSD-3-Clause","license_treatment":"permissive","name":"stockstats","python_support":"supports_current","summary":"DataFrame with inline stock statistics support."},"popularity":{"monthly_downloads":219665,"position":9322,"tier":"top_15000"},"security":{"n_vulnerabilities":0},"version":"0.6.8"}